Ant colony optimization for microgrid multi-objective power management

Colson, C.M.; Nehrir, M.H.; Wang, C.

doi:10.1109/psce.2009.4840070

Cited by 50 publications

(26 citation statements)

References 11 publications

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“…We give here a brief presentation of the two resolution approaches we are considering and explain how to apply them for solving (9). The interested reader will find more on those approaches in [4], [18].…”

Section: Presentation Of the Numerical Methodsmentioning

confidence: 99%

“…Furthermore, considering network constraints (load flow) adds another degree of complexity to the microgrid optimal energy management problem. To handle and solve these problem formulations, heuristic optimization techniques have been applied, including Genetic Algorithms (GA) [7], [8], PSO [7], and Ant Colony Optimization (ACO) [9]; the problem formulation has also been relaxed by incorporating the inequality constraints in the objective function using penalty factors. The minimization of total operating cost in stand-alone operation, and maximization of microgrids revenue in grid connected mode are two typically pursued objectives in secondary control.…”

Section: Introductionmentioning

confidence: 99%

“…In this case, the energy management problem is formulated as a multi-objective optimization problem and solved with different techniques [6]. Pareto optimal solutions are investigated in [9] and [10] by using PSO and ACO techniques, respectively, while a weighted objective function that combines different individual objective functions, together with heuristic optimization techniques, are used in [11], [12]. Finally, recent works, focusing on micro grid energy management systems, have incorporated a more detailed modeling of the energy storage system, considering the importance of the cost associated with its replacement, so that extending the life span of the battery is part of the objective.…”

Section: Introductionmentioning

confidence: 99%

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Continuous optimal control approaches to microgrid energy management

et al. 2017

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Abstract-We propose a novel method for the microgrid energy management problem by introducing a continuous-time, rolling horizon formulation. The energy management problem is formulated as a deterministic optimal control problem (OCP). We solve (OCP) with two classical approaches: the direct method [1], and Bellman's Dynamic Programming Principle (DPP) [2]. In both cases we use the optimal control toolbox BOCOP [3] for the numerical simulations. For the DPP approach we implement a semi-Lagrangian scheme [4] adapted to handle the optimization of switching times for the on/off modes of the diesel generator. The DPP approach allows for an accurate modeling and is computationally cheap. It finds the global optimum in less than 3 seconds, a CPU time similar to the Mixed Integer Linear Programming (MILP) approach used in [5]. We achieve this performance by introducing a trick based on the Pontryagin Maximum Principle (PMP). The trick increases the computation speed by several orders and also improves the precision of the solution. For validation purposes, simulation are performed using datasets from an actual isolated microgrid located in northern Chile. Results show that DPP method is very well suited for this type of problem when compared with the MILP approach.

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Section: Presentation Of the Numerical Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Continuous optimal control approaches to microgrid energy management

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“…[56]. Genetic algorithm [57], particle swarm optimization (PSO) [58][59][60][61], and ant colony optimization (ACO) [58,62] are also utilized as intelligent computational methods for microgrid power management and optimization.…”

Section: Microgrid Control Strategies Power Management and Optimizamentioning

confidence: 99%

“…However, interaction between all nodes within a microgrid including both conventional and renewable energy generation sources will not only increase the complexity of the power system considerably, but it will also raise challenging issues of reliability and power quality due to intermitent nature of renewable sources. Therefore, many technical challenges must yet be overcome to ensure safe, secure, reliable, optimized, eicient, and cost efective operation of the microgrid.Academic scholars and industry experts ofered many innovative techniques and technologies to address the challenges of microgrids such as power quality and power low balancing [3][4][5][6][7][8][9][10][11][12], voltage and frequency control , power management [36][37][38][39][40][41][42][43][44][45][46][47][48], optimization [49][50][51][52][53][54][55][56][57][58][59][60][61][62], stability [63][64][65][66], reliability and protection [67][68]…”

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confidence: 99%

Overview of Technical Challenges, Available Technologies and Ongoing Developments of AC/DC Microgrids

Sabzehgar¹

2017

Development and Integration of Microgrids

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Gradual depletion of fossil fuel resources, poor energy eiciency of conventional power plants, and environmental pollution have led to a new grid architecture known as smart microgrid. The smart microgrid concept provides a promising solution that enables high penetration of distributed generation from renewable energy sources without requiring to redesign the distribution system, which results in stable operation during faults and disturbances. However, distributed generators/loads and interaction between all nodes within a microgrid will substantially increase the complexity of the power system operation, control, and communications. Many innovative techniques and technologies have been proposed to address the complexity and challenges of microgrids including power quality, power low balancing, real-time power management, voltage and frequency control, load sharing during islanding, protection, stability, reliability, eiciency, and economical operation. All key issues of the microgrids, diferent solutions, and available methods and technologies to address such issues are reviewed in this chapter. Pros and cons of each method are discussed. Furthermore, an extensive comprehensive review for researchers and scholars working on microgrid applications is provided in this chapter to help them identify the areas that need improvements and innovative solutions for increasing the eiciency of modern power distribution grid.Keywords: AC microgrid, DC microgrid, microgrid power quality, power management, microgrid modeling, power electronics, renewable energies © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. IntroductionThe smart microgrid concept was irst developed in Refs. [1,2]. The capability of integration of a large number of distributed power generation sources and high penetration of renewable sources such as photovoltaic panels, wind turbines, and fuel cells within a smart microgrid made it very atractive. In fact, management of multiple distributed power generation sources including renewable energy sources in a smart microgrid ofers many advantages such as signiicant reduction in the need for a transmission and high voltage distribution system, satisfying the growing demand of electricity, and improving energy utilization eiciency and reliability. However, interaction between all nodes within a microgrid including both conventional and renewable energy generation sources will not only increase the complexity of the power system considerably, but it will also raise challenging issues of reliability and power quality due to intermitent nature of renewable sources. Therefore, many technical challenges must yet be overcome to ensure safe, secure, reliable, optimized, eicient, and cost efective operation of the microgrid.Academic scholars and industry experts ofe...

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